Automatic meter reading (AMR) allows data to be automatically collected from electric meters at residences and/or businesses and transmitted to a central database for billing, analyzing, and other purposes. Utility companies, or contracted agents of utility companies, typically use trucks equipped with AMR radio devices to capture electric meter data while driving past a residence or business. Alternatively, utility personnel or agents may walk within a certain proximity of the meter and capture the electric meter data via a handheld device. The captured data is processed by a utility company and is used to calculate a customer's electricity bill.
AMR meters commonly transmit data including, but not limited to, summation information, interval information, present demand, configuration, diagnostic information, and a meter identifier. Summation information is the total amount of the product (e.g., energy, water, natural gas, etc.) delivered to a home or business. A summation value may decrease over time, for example, when a home is equipped with solar panels or a windmill, allowing the consumer to return energy to a power grid. A billing scheme implemented by allowing the consumer to return energy to a power grid. A billing scheme implemented by a utility company may provide for more than one summation. For example, one summation may apply to weekdays, while another summation may apply to nights and weekends. A summation is expressed in a unit of measure that is appropriate for the asset being delivered, such as a multiple of watt-hours (Wh) for energy, gallons for water, or cubic feet for gas.
Interval information indicates the amount of product delivered in one or more preceding time periods. Each time period is equal in length, and the time periods usually begin with the most recent interval and proceed to less recent intervals within a defined period of time. For example, an AMR protocol may transmit data for ten (10) intervals, with each interval representing a period of time of 2.5 minutes. In such an example, the interval data allows for historical analysis of the product usage for the 25 minutes (10×2.5 minutes) prior to the data transmission. Interval data often includes an indication of the time at which the most recent interval ended. Interval data is expressed in units similar to summation data.
Present demand indicates the amount of an asset currently being delivered through the metering device. Due to the nature of this measurement, present demand is typically only reported by meters that measure electricity. Present demand is an indication of the total amount of power being consumed by all of the devices to which the meter is providing power, and is usually measured in a multiple of watts (W).
Meter configuration data allows a receiving device to determine how to parse data transmitted by the meter. Meter configuration data may include information such as how many units (e.g., watt-hours, gallons, cubic feet) are represented by each segment of summation or interval data, how frequently the meter will transmit a message, how many seconds each interval of interval data represents, and other information. Meter configuration data may also indicate the version of firmware running on the AMR meter, which allows a receiving device to adjust for the effects of any known bugs in that firmware version. Not all AMR meters transmit meter configuration data. Where meter configuration data is not transmitted, a receiving device may derive the configuration data from the data format, presuming that the meter is configured like meters that transmit data in a similar format.
A meter identifier (ID) designates the meter that transmitted the message. Meter IDs may vary in length, and a single meter may transmit messages corresponding to more than one meter ID. Where a meter transmits messages corresponding to multiple meter IDs, the meter typically has a base ID of n and transmits messages with message IDs corresponding to n, n+1, n+2, and so on.
AMR meter data may be encoded for transmission according to a variety of recognized methods, including amplitude modulation (AM), frequency modulation (FM), frequency-hopping spread spectrum (FHSS), direct sequence spread spectrum (DSSS), non-return-to-zero (NRZ), Manchester encoding, and other methods. Because these methods are well known in the art, they will not be described in additional detail herein.
Under current AMR technology, a customer does not have real-time access to consumption data. Instead, the customer typically only sees its consumption data as part of its bill. This impedes a customer's ability to manage and understand its resource usage.
Moreover, smart energy grids are increasingly being deployed in residences, businesses, and neighborhoods. In addition to delivering energy to a residence or business in the usual manner, a smart grid allows a utility provider to interact with its customers in near real-time, allowing greater visibility into energy utilization. This improved visibility in turn allows much-improved management of energy usage. In addition, it allows the utility to warn customers of anticipated peak usage situations, so that devices in the customer's home can be configured to automatically curtail energy usage. Accordingly, the impact of a peak usage situation, such as energy consumption on an extraordinarily hot day, may be lessened. One of the most common implementations of the customer side of a smart grid uses the ZigBee smart energy (SE) protocol. The ZigBee SE protocol allows information to be collected from a network of sensing and control devices within a residence or business. However, AMR meter data is not compatible with the ZigBee SE protocol. AMR meter data cannot be read by a ZigBee device, and thus cannot be incorporated into an information system that processes and presents usage information from ZigBee devices.